Alternatives to Genie 4
Compare Genie 4 alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Genie 4 in 2026. Compare features, ratings, user reviews, pricing, and more from Genie 4 competitors and alternatives in order to make an informed decision for your business.
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LTX
Lightricks
LTX is an open foundation model for video, audio, and world simulation. You get full control over your AI: run LTX locally on your own hardware, fine tune it on your own IP, and generate video and audio as one unified output instead of stitching together separate tools. The latest model, LTX-2.5, is a 22B-parameter dual-stream diffusion transformer that generates native 4K video at up to 50fps, with synchronized audio and video produced in a single pass. Weights, code, and research are fully open, and independent benchmarking from Artificial Analysis ranks LTX among the top 3 AI video models globally. Access LTX three ways: download the open weights and run it yourself, license the model for on-premise deployment with enterprise support, or build on LTX Studio, the production suite for creative teams and studios. Teams at ElevenLabs, Asteria Film Co., Magnopus, and NVIDIA already build on LTX. LTX is production infrastructure for AI teams generating motion and physical environments inside their own pipelines, not a consumer app for one-off clips. -
2
Gemini 4 Carbon
Google
Gemini 4 Carbon is an advanced multimodal AI reasoning model developed by Google DeepMind for cybersecurity, software engineering, scientific research, and autonomous agent workflows. Building on Gemini 4 Argon, the model delivers improved performance in vulnerability discovery, exploit validation, secure code generation, and automated software patching. Its long-horizon reasoning capabilities enable AI agents to work through complex engineering problems over extended periods, including debugging large codebases and resolving low-level system issues. Gemini 4 Carbon also supports full-stack web development, multimodal understanding, technical analysis, and multistep task execution. The model incorporates safety mechanisms for prompt injection resistance, monitoring, and alignment while reducing unsupported claims and unauthorized actions.Starting Price: $2 per 1M tokens (input) -
3
Gemini 4 Argon
Google
Gemini 4 Argon is a frontier artificial intelligence model developed by Google DeepMind for complex reasoning, software engineering, cybersecurity, and professional knowledge work. The model supports multimodal inputs, including text, images, audio, video, and PDF documents, with a unified context window of approximately one million tokens. Its advanced reasoning capabilities enable it to analyze difficult problems, maintain context across lengthy workflows, and execute multistep tasks. Gemini 4 Argon supports autonomous AI agents, code generation, application development, scientific research, and analysis of legal and financial information. Developer capabilities include function calling, code execution, structured outputs, search grounding, and preview support for computer use. The model is available through the Gemini API, Google AI Studio, Google Antigravity, and supported Gemini applications and enterprise services.Starting Price: $2 per 1M tokens (input) -
4
Gemini Omni
Google
Gemini Omni is a multimodal AI video generation and editing platform from Google designed to help users create cinematic-quality videos using text, image, and video inputs. The platform allows users to generate, edit, and enhance video content through natural language prompts without requiring advanced editing skills or expensive production equipment. Gemini Omni supports features such as cinematic zoom effects, background replacement, AI avatar creation, and template-based editing to simplify professional video production workflows. Users can upload footage directly from their devices and use conversational prompts to transform raw clips into polished visual content quickly and efficiently. The platform also enables users to create custom AI avatars that replicate their appearance and voice for more personalized video experiences. Built for creators and content producers, Gemini Omni helps users streamline video production while making high-quality AI-assisted editing more accessible. -
5
Gemini Omni Flash
Google
Gemini Omni is Google’s new model family where Gemini’s ability to reason meets the ability to create, starting with video. The first model in the family, Gemini Omni Flash, can create anything from any input by combining images, audio, video, and text as input, then generating high-quality videos grounded in Gemini’s real-world knowledge. It gives users an easier way to edit video through conversation, where every instruction builds on the last, characters stay consistent, physics hold up, and the scene remembers what came before. Users can transform specific details or entire worlds, reimagine action, add new characters or objects, change environments, adjust camera angles, refine styles, and build multi-turn edits without losing the thread of the original scene. Gemini Omni is designed to bridge photorealism and meaningful storytelling by reasoning about what should happen next, using an intuitive understanding of forces like gravity, kinetic energy, and fluid dynamics. -
6
Veo 3
Google
Veo 3 is Google’s latest state-of-the-art video generation model, designed to bring greater realism and creative control to filmmakers and storytellers. With the ability to generate videos in 4K resolution and enhanced with real-world physics and audio, Veo 3 allows creators to craft high-quality video content with unmatched precision. The model’s improved prompt adherence ensures more accurate and consistent responses to user instructions, making the video creation process more intuitive. It also introduces new features that give creators more control over characters, scenes, and transitions, enabling seamless integration of different elements to create dynamic, engaging videos. -
7
GWM-1
Runway AI
GWM-1 is Runway’s state-of-the-art General World Model designed to simulate the real world in real time. It is an interactive, controllable, and general-purpose model built on top of Runway’s Gen-4.5 architecture. GWM-1 generates high-fidelity video frame by frame while maintaining long-term spatial and behavioral consistency. The model supports action-conditioning through inputs such as camera movement, robot actions, events, and speech. GWM-1 enables realistic visual simulation paired with synchronized video and audio outputs. It is designed to help AI systems experience environments rather than just describe them. GWM-1 represents a major step toward general-purpose simulation beyond language-only models. -
8
Genie 3
Google DeepMind
Genie 3 is DeepMind’s next-generation, general-purpose world model capable of generating richly interactive 3D environments in real time at 24 frames per second and 720p resolution that remain consistent for several minutes. Prompted by text input, the system constructs dynamic virtual worlds where users (or embodied agents) can navigate and interact with natural phenomena from multiple perspectives, like first-person or isometric. A standout feature is its emergent long-horizon visual memory: Genie 3 maintains environmental consistency over extended durations, preserving off-screen elements and spatial coherence across revisits. It also supports “promptable world events,” enabling users to modify scenes, such as changing weather or introducing new objects, on the fly. Designed to support embodied agent research, Genie 3 seamlessly integrates with agents like SIMA, facilitating goal-based navigation and complex task accomplishment. -
9
NVIDIA Cosmos
NVIDIA
NVIDIA Cosmos is a developer-first platform of state-of-the-art generative World Foundation Models (WFMs), advanced video tokenizers, guardrails, and an accelerated data processing and curation pipeline designed to supercharge physical AI development. It enables developers working on autonomous vehicles, robotics, and video analytics AI agents to generate photorealistic, physics-aware synthetic video data, trained on an immense dataset including 20 million hours of real-world and simulated video, to rapidly simulate future scenarios, train world models, and fine‑tune custom behaviors. It includes three core WFM types; Cosmos Predict, capable of generating up to 30 seconds of continuous video from multimodal inputs; Cosmos Transfer, which adapts simulations across environments and lighting for versatile domain augmentation; and Cosmos Reason, a vision-language model that applies structured reasoning to interpret spatial-temporal data for planning and decision-making.Starting Price: Free -
10
Marble
World Labs
Marble is an experimental AI model internally tested by World Labs, a variant and extension of their Large World Model technology. It is a web service that turns a single 2D image into a navigable spatial environment. Marble offers two generation modes: a smaller, fast model for rough previews that’s quick to iterate on, and a larger, high-fidelity model that takes longer (around ten minutes in the example) but produces a significantly more convincing result. The value proposition is instant, photogrammetry-like image-to-world creation without a full capture rig, turning a single shot into an explorable space for memory capture, mood boards, archviz previews, or creative experiments. -
11
Mirage 2
Dynamics Lab
Mirage 2 is an AI-driven Generative World Engine that lets anyone instantly transform images or descriptions into fully playable, interactive game environments directly in the browser. Upload sketches, concept art, photos, or prompts, like “Ghibli-style village” or “Paris street scene”, and Mirage 2 builds immersive worlds you can explore in real time. The experience isn’t pre-scripted: you can modify your world mid-play using natural-language chat, evolving settings dynamically, from a cyberpunk city to a rainforest or a mountaintop castle, all with minimal latency (around 200 ms) on a single consumer GPU. Mirage 2 supports smooth rendering, real-time prompt control, and extended gameplay stretches beyond ten minutes. It outpaces earlier world-model systems by offering true general-domain generation, no upper limit on styles or genres, as well as seamless world adaptation and sharing features. -
12
Odyssey-2 Pro
Odyssey ML
Odyssey-2 Pro is a frontier general-purpose world model that generates continuous, interactive simulations you can integrate into products via the Odyssey API, marking a pivotal moment for world models similar to GPT-2 in language. It’s trained on large amounts of video and interaction data to learn how the world evolves frame-by-frame and outputs minutes-long simulations that can be interacted with in real time, not fixed short clips. Odyssey-2 Pro delivers improved physics, richer dynamics, more authentic behaviors, and sharper visuals by streaming 720p video at up to ~22 FPS that responds instantly to prompts and actions, and it supports embedding interactive streams, viewable streams, and parameterized simulations into applications with simple SDKs in JavaScript and Python. Developers can integrate the model with under ten lines of code to create open-ended, interactive video experiences where users’ inputs shape evolving scenes. -
13
Odyssey
Odyssey ML
Odyssey is a frontier interactive video model that enables instant, real-time generation of video you can interact with. Just type a prompt, and the system begins streaming minutes of video that respond to your input. It shifts video from a static playback format to a dynamic, action-aware stream: the model is causal and autoregressive, generating each frame based solely on prior frames and your actions rather than a fixed timeline, enabling continuous adaptation of camera angles, scenery, characters, and events. The platform begins streaming video almost instantly, producing new frames every ~50 milliseconds (about 20 fps), so you don’t wait minutes for a clip, you engage in an evolving experience. Under the hood, the model is trained via a novel multi-stage pipeline to transition from fixed-clip generation to open-ended interactive video, allowing you to type or speak commands and explore an AI-imagined world that reacts in real time. -
14
Project Genie
Google DeepMind
Project Genie is an experimental AI system from Google that generates interactive worlds in real time. It allows users to create living, explorable environments using simple text or image prompts. As you move through a world, Genie dynamically builds the landscape around you, making each experience unique. Users can design characters and choose how they explore, from walking and driving to flying and riding. The platform supports a wide range of environments, including natural landscapes, fictional worlds, and scenes generated from photos or artwork. Genie reacts to movement, physics, and user actions to create a continuous sense of discovery. Project Genie showcases the future of real-time, AI-generated interactive environments. -
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Odyssey-2 Max
Odyssey
Odyssey-2 Max is a scaled, real-time world simulation model designed to move beyond traditional generative AI by learning how the physical world behaves and enabling continuous, interactive environments. It represents the third and most advanced model in the Odyssey-2 family, significantly increasing scale with three times the parameters and ten times the training compute compared to Odyssey-2 Pro, which unlocks new emergent behaviors and more stable, realistic simulations. It is built to simulate physics, human motion, interaction, and environmental dynamics in real time, generating continuous streams of visual output that respond instantly to user input instead of producing fixed clips. Unlike conventional video models that generate short, precomputed sequences, Odyssey-2 Max produces long-running simulations that evolve frame by frame, allowing users to interact with the environment as it unfolds. -
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Agora-1
Odyssey
Agora-1 is a multi-agent world model that enables multiple participants, human or AI, to share and interact within the same world simulation in real time. It is the first in a series of multi-agent world models exploring how world models can enable new shared experiences across gaming, robotics, defense, education, foundation models, and more. World models generate high-fidelity simulations of arbitrary environments, but until now, they have largely been limited to a single active participant inside those simulated worlds. Agora-1 introduces multi-agent world simulations by allowing up to four players to interact in the same generated world at once. Players are matched into a shared deathmatch simulation, where every participant interacts with the same world simultaneously while the model simulates player actions, maintains shared world state, and streams generated pixels to each player. -
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Happy Oyster
Alibaba
Happy Oyster is an open-ended AI “world model” platform designed for real-time world creation and interaction, enabling users to generate, explore, and continuously evolve immersive 3D environments from simple prompts. Instead of producing a fixed output, it operates as a living system that responds dynamically to user input, allowing scenes to update in real time as instructions are given through text, voice, or images. It supports multimodal interaction and maintains consistent physical logic, including lighting, gravity, motion, and scene continuity, so that generated environments behave like coherent, persistent worlds rather than isolated clips. It introduces two core modes: Directing, where users actively control scenes, adjust camera angles, guide characters, and shape narratives as they unfold; and Wandering, where users can freely explore an infinitely extendable world in a first-person perspective, moving beyond initial frames.Starting Price: Free -
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Gemini Robotics-ER 1.6
Google DeepMind
Gemini Robotics-ER 1.6 is a family of AI models developed by Google DeepMind to bring advanced multimodal intelligence into the physical world by enabling robots to perceive, reason, and act in real-world environments. Built on the Gemini 2.0 foundation, it extends traditional AI capabilities by adding physical action as an output modality, allowing robots to interpret visual input and natural language instructions and convert them directly into motor commands to complete tasks. It includes a vision-language-action model that processes images and instructions to execute tasks, as well as a complementary embodied reasoning model (Gemini Robotics-ER) that specializes in spatial understanding, planning, and decision-making within physical environments. These models enable robots to generalize across new situations, objects, and environments, allowing them to perform complex, multi-step tasks even if they were not explicitly trained for them. -
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Reactor
Reactor
Reactor is building the missing layer for world models and invites users to experience real-time world models through an early preview. Its product direction centers on worlds generated in real time, where pixels, sounds, and actions can be produced on the fly, changing how people interact with software and, eventually, the physical world. The preview is the first step toward that reality, letting users experience AI-generated worlds running on global low-latency infrastructure. Reactor’s work is focused on the next frontier of AI, real-time world models that people, agents, and robots can drive frame by frame. Rather than treating generated video as something passive to watch, Reactor points toward interactive environments that can be inhabited, controlled, and shaped as they generate. Its research and product focus includes real-time interactivity, inference, controllable world models, and systems that make dynamic visual environments responsive enough for live experiences.Starting Price: Free -
20
spAItial
spAItial
SpAItial is an AI platform focused on building and deploying Spatial Foundation Models (SFMs), a new class of generative AI systems designed to create and understand 3D environments with physical realism and spatial awareness. Unlike traditional models that generate pixels or text independently, SpAItial’s technology operates directly on 3D structures, capturing geometry, materials, lighting, and physics from the outset to produce coherent, interactive worlds. Its flagship model, Echo-2, can transform a single image into a fully explorable, photorealistic 3D scene using techniques like Gaussian splatting, enabling users to navigate and render environments in real time. It is built around a physically grounded understanding of space-time, allowing AI to reason about how objects exist, interact, and evolve within an environment rather than producing disconnected outputs. This approach reduces inconsistencies common in traditional generative AI and enables more accurate simulation.Starting Price: Free -
21
Starchild-1
Odyssey
Starchild-1 is the first real-time multimodal world model, built to simulate both the visuals and sounds of the world in real time. Unlike language models, which learn from text, world models learn directly from the world itself through pixels, motion, and actions encoded in large-scale video, becoming capable of understanding and simulating an approximation of the world as it evolves. Starchild-1 goes beyond traditional world models, which have mostly focused on visual generation alone, by autoregressively generating synchronized audio and video while continuously responding to streaming user input. Instead of producing a fixed offline clip, it predicts the next audio and video state of a world based on past observations and live inputs, enabling environments, conversations, ambient sound, and world dynamics to change interactively. Users can stream text, speech, and action inputs into the model during rollout, dynamically altering what is seen and heard in real time. -
22
HunyuanWorld
Tencent
HunyuanWorld-1.0 is an open source AI framework and generative model developed by Tencent Hunyuan that creates immersive, explorable, and interactive 3D worlds from text prompts or image inputs by combining the strengths of 2D and 3D generation techniques into a unified pipeline. At its core, the project features a semantically layered 3D mesh representation that uses 360° panoramic world proxies to decompose and reconstruct scenes with geometric consistency and semantic awareness, enabling the creation of diverse, coherent environments that can be navigated and interacted with. Unlike traditional 3D generation methods that struggle with either limited diversity or inefficient data representations, HunyuanWorld-1.0 integrates panoramic proxy generation, hierarchical 3D reconstruction, and semantic layering to balance high visual quality and structural integrity while enabling exportable meshes compatible with common graphics workflows.Starting Price: Free -
23
Atlas by World Labs
World Labs
Atlas is a next-generation omni world model for spatial intelligence that natively operates on text, images, video, and 3D. Built as a multimodal autoregressive diffusion transformer, it combines inputs into a shared spatial context and generates what comes next while staying consistent in 3D with everything it has seen and imagining what lies beyond it. Atlas supports world generation, reconstruction, and simulation across a broad range of tasks. It can generate images and videos from one or more reference images with pixel-perfect camera control, producing long, coherent videos with manually designed camera paths. For spatial reconstruction, Atlas can recreate real-world scenes from sparse input images, generate novel views, and produce explicit 3D outputs such as point clouds and 3D Gaussian splats. More input views provide additional context, allowing the model to reduce imagination and create increasingly faithful reconstructions. Atlas also models how worlds evolve over time. -
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Odyssey-3
Odyssey
Odyssey-3 is a foundation world model and learned dynamical system that predicts how objects move and interact through space and how situations evolve over time. Implemented as an autoregressive diffusion transformer, it learns representations of physics, dynamics, and cause-and-effect from a broad dataset of visual observations and uses that knowledge to simulate environments and train policies for physical systems. Odyssey-3 can generate embodied environments from a prompt and predict in real time how they change as a person or agent acts or introduces events, with first-person and third-person navigation and independent camera movement. Its learned world knowledge can be adapted to different systems by training an action decoder or policy on paired observations and actions. With relatively small amounts of task-specific data, Odyssey-3 has been used to control robot arms, power humanoids, drive vehicles, and generate synchronized multi-sensor observations. -
25
Gemini Flash
Google
Gemini Flash is an advanced large language model (LLM) from Google, specifically designed for high-speed, low-latency language processing tasks. Part of Google DeepMind’s Gemini series, Gemini Flash is tailored to provide real-time responses and handle large-scale applications, making it ideal for interactive AI-driven experiences such as customer support, virtual assistants, and live chat solutions. Despite its speed, Gemini Flash doesn’t compromise on quality; it’s built on sophisticated neural architectures that ensure responses remain contextually relevant, coherent, and precise. Google has incorporated rigorous ethical frameworks and responsible AI practices into Gemini Flash, equipping it with guardrails to manage and mitigate biased outputs, ensuring it aligns with Google’s standards for safe and inclusive AI. With Gemini Flash, Google empowers businesses and developers to deploy responsive, intelligent language tools that can meet the demands of fast-paced environments. -
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WorldClaw
Tencent
WorldClaw is a fully agentic, coarse-to-fine framework for generating large-scale, freely explorable, and editable 3D open worlds from open-ended text prompts. Rather than synthesizing an entire world in a single pass, it follows a global-to-regional construction strategy that maintains coherent spatial organization while adding rich local detail. Planning agents first translate a prompt into a structured scene specification covering regions, terrain, assets, materials, visual style, and spatial relationships. It builds a globally coherent terrain foundation using semantic layouts, reusable assets, generative or procedural materials, and region-aware height fields. For regions requiring greater detail, WorldClaw creates terrain-conditioned compositions, reconstructs editable textured meshes, and recovers their placement within the scene. Render-based agents further refine terrain geometry, objects, appearance, arrangements, and contacts with the environment.Starting Price: Free -
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Gemini 3.1 Flash Live
Google
Gemini 3.1 Flash Live is Google’s most advanced real-time audio model, designed to deliver natural, reliable, and low-latency voice interactions for the next generation of conversational AI. It is optimized for real-time dialogue, enabling fluid, human-like conversations with improved precision, faster response times, and a more natural rhythm that better reflects how people actually speak. It enhances tonal understanding, allowing it to recognize nuances such as pitch, pace, and emotional cues, and dynamically adapt responses to user intent, including frustration or confusion. Built for both developers and enterprises, it can be accessed through the Gemini Live API in Google AI Studio, as well as integrated into production environments to power voice-first agents capable of handling complex, multi-step tasks at scale. It supports multimodal inputs including text, audio, images, and video, and produces both text and audio outputs, enabling richer, context-aware interactions. -
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FLUX 3 Action
Black Forest Labs
FLUX 3 Action is an open-weight 7B world-action model designed for action prediction in robotics and other latency-sensitive visual environments. Derived from the multimodal FLUX 3 backbone, it was pretrained on large-scale image, video, and audio data with a strong emphasis on video, then adapted through joint video-action training and fine-tuning for specific embodiments and action spaces. Given an instruction, camera observations, and robot joint positions, the model predicts motor commands together with their expected visual outcomes, allowing a robot to execute actions, observe the environment again, and continuously replan. Unlike approaches that separate visual prediction from control, FLUX 3 Action jointly models future video and actions, transferring world understanding learned from broad video pretraining into robot control. Its single-step 7B checkpoint reaches a 38.3% success rate on RoboLab-120. -
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Gemini Robotics 2
Google DeepMind
Gemini Robotics 2 is Google DeepMind’s intelligence layer for adaptable robots, bringing whole-body control, advanced dexterity, embodied reasoning, and multi-robot collaboration to physical AI. It includes three models. Gemini Robotics 2 is a vision-language-action model that converts visual and language input into motor control, enabling humanoids and bi-arm robots to act from feet to fingertips. It can coordinate walking, crouching, reaching, balancing, and object manipulation, while controlling five-fingered hands or standard grippers for delicate and precise tasks. Gemini Robotics ER 2 serves as the high-level brain, communicating with people, understanding its surroundings, planning multi-step tasks that last several minutes, coordinating actions with the VLA, tracking progress, self-correcting failures, and allowing different robots to work together. -
30
Gemini 3 Deep Think
Google
The most advanced model from Google DeepMind, Gemini 3, sets a new bar for model intelligence by delivering state-of-the-art reasoning and multimodal understanding across text, image, and video. It surpasses its predecessor on key AI benchmarks and excels at deeper problems such as scientific reasoning, complex coding, spatial logic, and visual-/video-based understanding. The new “Deep Think” mode pushes the boundaries even further, offering enhanced reasoning for very challenging tasks, outperforming Gemini 3 Pro on benchmarks like Humanity’s Last Exam and ARC-AGI. Gemini 3 is now available across Google’s ecosystem, enabling users to learn, build, and plan at new levels of sophistication. With context windows up to one million tokens, more granular media-processing options, and specialized configurations for tool use, the model brings better precision, depth, and flexibility for real-world workflows. -
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Gemini 2.5 Flash Image
Google
Gemini 2.5 Flash Image is Google’s latest state-of-the-art image generation and editing model, now accessible via the Gemini API, Google AI Studio’s build mode, and Gemini Enterprise Agent Platform. It enables powerful creative control by allowing users to blend multiple input images into a single visual, maintain consistent characters or products across edits for rich storytelling, and apply precise, natural-language-based–based transformations, such as removing objects, changing poses, adjusting colors, or altering backgrounds. The model is backed by Gemini’s deep world knowledge, enabling it to understand and reinterpret scenes or diagrams in context, which unlocks dynamic use cases like educational tutors or scene-aware editing assistants. Demonstrated through customizable template apps in AI Studio (including photo editors, multi-image fusers, and interactive tools), the model supports rapid prototyping and remixing via prompts or UI. -
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Google AI Ultra
Google
Google AI Ultra is Google’s highest-tier AI subscription plan that provides maximum access to advanced Gemini models, AI-powered creative tools, agentic AI capabilities, developer platforms, and premium productivity features. Designed for power users, developers, creators, and enterprises, the plan includes significantly higher usage limits, Gemini Spark access, Project Genie, premium Google Flow credits, advanced coding tools, and cloud storage starting at 20 TB across Google services.Starting Price: $99.99/month -
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Gemini 3.1 Flash Image
Google
Gemini 3.1 Flash Image is Google DeepMind’s latest image generation model, combining advanced Pro-level capabilities with lightning-fast performance. It delivers enhanced world knowledge, enabling more accurate subject rendering and data-informed visuals grounded in real-time information. The model improves precision text rendering and in-image translation, making it well-suited for marketing assets, infographics, and localized creative content. Stronger instruction following ensures complex prompts are executed with clarity and accuracy. Gemini 3.1 Flash Image maintains subject consistency across multiple characters and objects within a single workflow. It supports production-ready outputs with customizable aspect ratios and resolutions up to 4K. Available across Gemini, Search, AI Studio, Google Cloud, and more, it brings high-quality visual generation at Flash-level speed. -
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Gemini 3.8 Live
Google
Gemini 3.8 Live is Google DeepMind’s real-time speech-to-speech AI model for building conversational voice applications and interactive agents. The model can maintain natural dialogue while reasoning, using tools, and carrying out tasks during an ongoing conversation. Asynchronous function calling allows applications to execute API and tool requests in the background while Gemini continues streaming audio responses to the user. Gemini 3.8 Live can also incorporate live visual context, enabling agents to respond based on what users say and what the system can see. It supports more than 97 languages, maintains accent consistency, and is designed to accurately interpret alphanumeric information such as confirmation codes, claim numbers, and technical data. Gemini 3.8 Live is available through the Gemini Live API and Google AI Studio for developers building customer service agents, assistants, training applications, and other voice-first experiences. -
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Nano Banana 2
Google
Nano Banana 2 is Google DeepMind’s latest image generation model, combining the advanced capabilities of Nano Banana Pro with the high-speed performance of Gemini Flash. It delivers improved world knowledge, enabling more accurate subject rendering and data-driven visuals grounded in real-time information. The model enhances precision text rendering and translation, making it ideal for marketing assets, infographics, and localized content. Users benefit from stronger instruction following, ensuring complex prompts are captured accurately. Nano Banana 2 supports subject consistency across multiple characters and objects within a single workflow. It offers production-ready output with customizable aspect ratios and resolutions up to 4K. Available across Gemini, Search, AI Studio, Google Cloud, and more, Nano Banana 2 brings high-quality visual generation at lightning-fast speed. -
36
Gemini 2.0 Pro
Google
Gemini 2.0 Pro is Google DeepMind's most advanced AI model, designed to excel in complex tasks such as coding and intricate problem-solving. Currently in its experimental phase, it features an extensive context window of two million tokens, enabling it to process and analyze vast amounts of information efficiently. A standout feature of Gemini 2.0 Pro is its seamless integration with external tools like Google Search and code execution environments, enhancing its ability to provide accurate and comprehensive responses. This model represents a significant advancement in AI capabilities, offering developers and users a powerful resource for tackling sophisticated challenges. -
37
Gemini 2.0
Google
Gemini 2.0 is an advanced AI-powered model developed by Google, designed to offer groundbreaking capabilities in natural language understanding, reasoning, and multimodal interactions. Building on the success of its predecessor, Gemini 2.0 integrates large language processing with enhanced problem-solving and decision-making abilities, enabling it to interpret and generate human-like responses with greater accuracy and nuance. Unlike traditional AI models, Gemini 2.0 is trained to handle multiple data types simultaneously, including text, images, and code, making it a versatile tool for research, business, education, and creative industries. Its core improvements include better contextual understanding, reduced bias, and a more efficient architecture that ensures faster, more reliable outputs. Gemini 2.0 is positioned as a major step forward in the evolution of AI, pushing the boundaries of human-computer interaction.Starting Price: Free -
38
WeatherNext
Google DeepMind
WeatherNext is a family of AI models from Google DeepMind and Google Research that produces state-of-the-art weather forecasts. These models are faster and more efficient than traditional physics-based weather models and yield superior forecast reliability. The gains in forecast performance could enable better preparation to help save lives in the face of extreme weather events and enhance the reliability of sustainable energy and supply chains. WeatherNext Graph offers more accurate and efficient deterministic forecasts compared to the best deterministic systems in use today, providing a single weather forecast per time and location with a temporal resolution of 6 hours and a lead time of 10 days. WeatherNext Gen accurately generates an ensemble forecast, better than the current ensemble models most widely used today, helping decision-makers better understand weather uncertainties and risks of extreme conditions. -
39
Gemini 3.5 Flash-Lite
Google
Gemini 3.5 Flash-Lite is Google’s fastest model in the Gemini 3.5 series, designed for low-latency tasks and high-throughput developer workflows such as agentic search, document processing, coding, and large-scale data analysis. It delivers 350 output tokens per second and significantly improves on previous Flash-Lite generations in both quality and agentic performance. Developers can configure its thinking level to match the workload: minimal or low thinking supports fast execution for high-volume tasks, while higher thinking levels enable more complex, multi-step subagent workflows. Built-in computer-use capabilities allow the model to interact reliably with digital environments across supported surfaces. Gemini 3.5 Flash-Lite also advances coding, long-context understanding, and real-world task execution, outperforming Gemini 3.1 Flash-Lite across key evaluations and even surpassing Gemini 3 Flash on several agentic and software-engineering benchmarks.Starting Price: $0.30 per 1M input tokens -
40
Sora
OpenAI
Sora is an AI model that can create realistic and imaginative scenes from text instructions. We’re teaching AI to understand and simulate the physical world in motion, with the goal of training models that help people solve problems that require real-world interaction. Introducing Sora, our text-to-video model. Sora can generate videos up to a minute long while maintaining visual quality and adherence to the user’s prompt. Sora is able to generate complex scenes with multiple characters, specific types of motion, and accurate details of the subject and background. The model understands not only what the user has asked for in the prompt, but also how those things exist in the physical world. -
41
Gemini 3.5 Flash
Google
Gemini 3.5 Flash is Google’s latest frontier AI model designed to combine advanced intelligence, high-speed performance, and agentic workflow execution for developers, enterprises, and everyday users. Built as part of the Gemini 3.5 family, the model excels at coding, long-horizon reasoning, multimodal understanding, and complex multi-step automation tasks while delivering significantly faster output speeds than many competing frontier models. Gemini 3.5 Flash powers AI agents capable of planning, executing, and managing workflows such as application development, codebase maintenance, data analysis, and financial document preparation through the Antigravity harness. The model also supports rich multimodal experiences by generating interactive graphics, dynamic web interfaces, animations, and advanced visual content. Gemini 3.5 Flash is integrated across Google products including the Gemini app, Google Search AI Mode, Google Antigravity, Google AI Studio, Android Studio, and more.Starting Price: $1.50 per 1M tokens (input) -
42
Gemini 2.5 Flash-Lite
Google
Gemini 2.5 is Google DeepMind’s latest generation AI model family, designed to deliver advanced reasoning and native multimodality with a long context window. It improves performance and accuracy by reasoning through its thoughts before responding. The model offers different versions tailored for complex coding tasks, fast everyday performance, and cost-efficient high-volume workloads. Gemini 2.5 supports multiple data types including text, images, video, audio, and PDFs, enabling versatile AI applications. It features adaptive thinking budgets and fine-grained control for developers to balance cost and output quality. Available via Google AI Studio and Gemini API, Gemini 2.5 powers next-generation AI experiences. -
43
Gemini Deep Research Max
Google
Gemini Deep Research is Google’s next-generation autonomous research agent, designed to plan, execute, and synthesize complex, multi-step research tasks across the web and private data sources into high-quality, structured outputs. Built on top of advanced Gemini models such as Gemini 3.1 Pro, it introduces a system where the AI can break down a user’s query into sub-tasks, search across multiple sources, evaluate relevance, and iteratively refine results before producing a comprehensive, cited report. It is positioned as a “step change” in long-horizon research workflows, enabling autonomous exploration of both public web content and custom enterprise data while maintaining context and coherence across extended reasoning chains. It supports features such as MCP (Model Context Protocol) integration, native visualizations, and significantly improved analytical quality, allowing users to generate insights.Starting Price: Free -
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Databricks Genie Code
Databricks
Genie Code is an AI agent built for data teams that analyzes, builds, and maintains complex data workflows inside the Databricks workspace. It autonomously plans and executes multistep tasks while adapting to an organization’s data and governance model, with specialized capabilities across data engineering, data science, machine learning, and business intelligence. Grounded in Unity Catalog metadata, semantics, and governance, it can identify authoritative tables, metrics, and assets, understand dependencies across data and AI systems, and respect existing access controls. For data science, Genie Code can find and clean data, explore datasets, test hypotheses, and generate shareable reports. Machine learning workflows include feature engineering, model training and evaluation, deployment, endpoint configuration, and performance tuning. Data engineers can use natural language to automate ETL workloads, optimize queries, and build Spark Declarative Pipelines. -
45
Lyria 3 Pro
Google
Lyria 3 Pro is an advanced AI music generation model developed by Google DeepMind that enables users to create longer, high-quality music tracks with enhanced structure and control. It allows the generation of tracks up to three minutes long, supporting detailed composition elements such as intros, verses, choruses, and bridges. The model is designed to better understand musical structure, making it easier to produce cohesive and dynamic audio outputs. Lyria 3 Pro is integrated across multiple Google platforms, including Gemini Enterprise Agent Platform, Google AI Studio, and the Gemini app. It supports a wide range of use cases, from content creation and video production to large-scale audio generation for businesses. The model also includes safeguards to prevent imitation of specific artists and ensures responsible AI usage through built-in protections and watermarking. Overall, Lyria 3 Pro enhances creative workflows by providing powerful, customizable music generation capabilities. -
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Google has released updated Gemini audio models that significantly expand the platform’s capabilities for natural, expressive voice interactions and real-time conversational AI with the introduction of Gemini 2.5 Flash Native Audio and improved text-to-speech technology. The updated native audio model powers live voice agents that can handle complex workflows, follow detailed user instructions more reliably, and maintain smoother multi-turn conversations by better recalling context from previous turns. It is now available across Google AI Studio,Gemini Enterprise Agent Platform, Gemini Live, and Search Live, enabling developers and products to build interactive voice experiences such as intelligent assistants and enterprise voice agents. In addition to the real-time voice improvements, Google enhanced the underlying Text-to-Speech (TTS) models in the Gemini 2.5 family to offer greater expressivity, tone control, pacing adjustments, and multilingual support.
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Gemini 2.5 Flash TTS
Google
Gemini 2.5 Flash TTS is the latest text-to-speech (TTS) model variant in Google’s Gemini 2.5 lineup, designed for faster, low-latency speech synthesis with expressive, controllable audio output. It offers significant enhancements in tone versatility and expressivity so that developers can generate speech that better matches style prompts, from storytelling narrations to character voices, with more natural emotional range. It features precision pacing, which allows it to adjust speech tempo based on context, delivering faster sections or slowing for emphasis more accurately according to instructions. It also supports multi-speaker dialogues with consistent character voices for scenarios like podcasts, interviews, or conversational agents, and improved multilingual handling so each speaker’s unique tone and style persist across languages. Gemini 2.5 Flash TTS is optimized for lower latency, making it ideal for interactive applications and real-time voice interfaces. -
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Lyria 3
Google
Lyria 3 is Google DeepMind’s most advanced AI music generation model, designed to create high-fidelity, professional-grade audio from simple prompts. It enables users to describe a track in natural language and refine details such as tempo, vocal style, and instrumentation for greater creative control. The model can generate cohesive songs that flow naturally from start to finish across a wide range of genres and global languages. Lyria 3 also supports image-to-music composition, allowing users to upload visuals and transform them into custom soundtracks. Built with input from musicians and producers, it understands rhythm, arrangement, and musical structure at a deeper level. Users can export crisp, polished tracks suitable for background ambience, content creation, or mainstage productions. Integrated into Gemini and other creative tools, Lyria 3 empowers creators to explore, experiment, and express ideas through AI-driven music. -
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Gemma
Google
Gemma is a family of lightweight, state-of-the-art open models built from the same research and technology used to create the Gemini models. Developed by Google DeepMind and other teams across Google, Gemma is inspired by Gemini, and the name reflects the Latin gemma, meaning “precious stone.” Accompanying our model weights, we’re also releasing tools to support developer innovation, foster collaboration, and guide the responsible use of Gemma models. Gemma models share technical and infrastructure components with Gemini, our largest and most capable AI model widely available today. This enables Gemma 2B and 7B to achieve best-in-class performance for their sizes compared to other open models. And Gemma models are capable of running directly on a developer laptop or desktop computer. Notably, Gemma surpasses significantly larger models on key benchmarks while adhering to our rigorous standards for safe and responsible outputs. -
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Gemini 3.8 Flash-Lite TTS
Google
Gemini 3.8 Flash-Lite TTS is Google’s cost-efficient text-to-speech model designed for high-volume dubbing, audio production, and expressive voice-agent applications. The model provides fine-grained control over tone, pacing, expressive nuance, and line-by-line vocal delivery. It supports long-form speech generation while maintaining natural pacing, voice quality, and speaker consistency across extended content. Native two-speaker scene staging enables multi-turn dialogue with distinct voices and natural conversational turn-taking from a single script. Gemini 3.8 Flash-Lite TTS supports more than 100 languages and can add nonverbal cues and backchanneling to create more natural conversational audio. The model is available through the Gemini API and Google AI Studio, with deployment through Google Vids and planned enterprise availability through Gemini Enterprise.
